Detecting latency differences in event-related BOLD responses: application to words versus nonwords and initial versus repeated face presentations

Pros and Cons of Using the Informed Basis Set to Account for Hemodynamic Response Variability with Developmental Data

Conventional analysis of functional magnetic resonance imaging (fMRI) data using the general linear model (GLM) employs a neural model convolved with a canonical hemodynamic response function (HRF) peaking 5 s after stimulation. Incorporation of a further basis function, namely the canonical HRF temporal derivative, accounts for delays in the hemodynamic response to neural activity. A population that may benefit from this flexible approach is children whose hemodynamic response is not yet mature. Here, we examined the effects of using the set based on the canonical HRF plus its temporal derivative on both first- and second-level GLM analyses, through simulations and using developmental data (an fMRI dataset on proprioceptive mapping in children and adults). Simulations of delayed fMRI first-level data emphasized the benefit of carrying forward to the second-level a derivative boost that combines derivative and nonderivative beta estimates. In the experimental data, second-level analysis using a paired t-test showed increased mean amplitude estimate (i.e., increased group contrast mean) in several brain regions related to proprioceptive processing when using the derivative boost compared to using only the nonderivative term. This was true especially in children. However, carrying forward to the second-level the individual derivative boosts had adverse consequences on random-effects analysis that implemented one-sample t-test, yielding increased between-subject variance, thus affecting group-level statistic. Boosted data also presented a lower level of smoothness that had implication for the detection of group average activation. Imposing soft constraints on the derivative boost by limiting the time-to-peak range of the modeled response within a specified range (i.e., 4–6 s) mitigated these issues. These findings support the notion that there are pros and cons to using the informed basis set with developmental data.

Altered Neural Correlate of the Self-Agency Experience in First-Episode Schizophrenia-Spectrum Patients: An fMRI Study

BACKGROUND

The phenomenology of the clinical symptoms indicates that disturbance of the sense of self be a core marker of schizophrenia.

AIMS

To compare neural activity related to the self/other-agency judgment in patients with first-episode schizophrenia-spectrum disorders (FES, n = 35) and healthy controls (HC, n = 35).

METHOD

A functional magnetic resonance imaging (fMRI) using motor task with temporal distortion of the visual feedback was employed. A task-related functional connectivity was analyzed with the use of independent component analysis (ICA).

RESULTS

(1) During self-agency experience, FES showed a deficit in cortical activation in medial frontal gyrus (BA 10) and posterior cingulate gyrus, (BA 31; P < .05, Family-Wise Error [FWE] corrected). (2) Pooled-sample task-related ICA revealed that the self/other-agency judgment was dependent upon anti-correlated default mode and central-executive networks (DMN/CEN) dynamic switching. This antagonistic mechanism was substantially impaired in FES during the task.

DISCUSSION

During self-agency experience, FES demonstrate deficit in engagement of cortical midline structures along with substantial attenuation of anti-correlated DMN/CEN activity underlying normal self/other-agency discriminative processes.

Central Nervous System Control of Voice and Swallowing

This review of the central nervous control systems for voice and swallowing has suggested that the traditional concepts of a separation between cortical and limbic and brain stem control should be refined and be more integrative. For voice production, a separation of the nonhuman vocalization system from the human learned voice production system has been posited based primarily on studies of nonhuman primates. However, recent humans studies of emotionally based vocalizations and human volitional voice production have shown more integration between these two systems than previously proposed. Recent human studies have shown that reflexive vocalization as well as learned voice production not involving speech involve a common integrative system. However, recent studies of nonhuman primates have provided evidence that some cortical activity vocalization and cortical changes occur with training during vocal behavior. For swallowing, evidence from the macaque and functional brain imaging in humans indicates that the control for the pharyngeal phase of swallowing is not primarily under brain stem mechanisms as previously proposed. Studies suggest that the initiation and patterning of swallowing for the pharyngeal phase is also under active cortical control for both spontaneous as well as volitional swallowing in awake humans and nonhuman primates.

Building a Science of Individual Differences from fMRI

To date, fMRI research has been concerned primarily with evincing generic principles of brain function through averaging data from multiple subjects. Given rapid developments in both hardware and analysis tools, the field is now poised to study fMRI-derived measures in individual subjects, and to relate these to psychological traits or genetic variations. We discuss issues of validity, reliability and statistical assessment that arise when the focus shifts to individual subjects and that are applicable also to other imaging modalities. We emphasize that individual assessment of neural function with fMRI presents specific challenges and necessitates careful consideration of anatomical and vascular between-subject variability as well as sources of within-subject variability.

Amygdala subnuclei response and connectivity during emotional processing

The involvement of the human amygdala in emotion-related processing has been studied using functional magnetic resonance imaging (fMRI) for many years. However, despite the amygdala being comprised of several subnuclei, most studies investigated the role of the entire amygdala in processing of emotions. Here we combined a novel anatomical tracing protocol with event-related high-resolution fMRI acquisition to study the responsiveness of the amygdala subnuclei to negative emotional stimuli and to examine intra-amygdala functional connectivity. The greatest sensitivity to the negative emotional stimuli was observed in the centromedial amygdala, where the hemodynamic response amplitude elicited by the negative emotional stimuli was greater and peaked later than for neutral stimuli. Connectivity patterns converge with extant findings in animals, such that the centromedial amygdala was more connected with the nuclei of the basal amygdala than with the lateral amygdala. Current findings provide evidence of functional specialization within the human amygdala.

Can predictive coding explain repetition suppression?

While in earlier work various local or bottom-up neural mechanisms were proposed to give rise to repetition suppression (RS), current theories suggest that top-down processes play a role in determining the repetition related reduction of the neural responses. In the current review we summarise those results, which support the role of these top-down processes, concentrating on the Bayesian models of predictive coding (PC). Such models assume that RS is related to the statistical probabilities of prior stimulus occurrences and to the future predictability of these stimuli. Here we review the current results that support or argue against this explanation. We point out that the heterogeneity of experimental manipulations that are thought to reflect predictive processes are likely to measure different processing steps, making their direct comparison difficult. In addition we emphasize the importance of identifying these sub-processes and clarifying their role in explaining RS. Finally, we propose a two-stage model for explaining the relationships of repetition and expectation phenomena in the human cortex.

How learning shapes the empathic brain

Deficits in empathy enhance conflicts and human suffering. Thus, it is crucial to understand how empathy can be learned and how learning experiences shape empathy-related processes in the human brain. As a model of empathy deficits, we used the well-established suppression of empathy-related brain responses for the suffering of out-groups and tested whether and how out-group empathy is boosted by a learning intervention. During this intervention, participants received costly help equally often from an out-group member (experimental group) or an in-group member (control group). We show that receiving help from an out-group member elicits a classical learning signal (prediction error) in the anterior insular cortex. This signal in turn predicts a subsequent increase of empathy for a different out-group member (generalization). The enhancement of empathy-related insula responses by the neural prediction error signal was mediated by an establishment of positive emotions toward the out-group member. Finally, we show that surprisingly few positive learning experiences are sufficient to increase empathy. Our results specify the neural and psychological mechanisms through which learning interacts with empathy, and thus provide a neurobiological account for the plasticity of empathic reactions.

The multisensory function of the human primary visual cortex

It has been nearly 10 years since Ghazanfar and Schroeder (2006) proposed that the neocortex is essentially multisensory in nature. However, it is only recently that sufficient and hard evidence that supports this proposal has accrued. We review evidence that activity within the human primary visual cortex plays an active role in multisensory processes and directly impacts behavioural outcome. This evidence emerges from a full pallet of human brain imaging and brain mapping methods with which multisensory processes are quantitatively assessed by taking advantage of particular strengths of each technique as well as advances in signal analyses. Several general conclusions about multisensory processes in primary visual cortex of humans are supported relatively solidly. First, haemodynamic methods (fMRI/PET) show that there is both convergence and integration occurring within primary visual cortex. Second, primary visual cortex is involved in multisensory processes during early post-stimulus stages (as revealed by EEG/ERP/ERFs as well as TMS). Third, multisensory effects in primary visual cortex directly impact behaviour and perception, as revealed by correlational (EEG/ERPs/ERFs) as well as more causal measures (TMS/tACS). While the provocative claim of Ghazanfar and Schroeder (2006) that the whole of neocortex is multisensory in function has yet to be demonstrated, this can now be considered established in the case of the human primary visual cortex.

Neuronal or hemodynamic? Grappling with the functional MRI signal

Magnetic resonance imaging (MRI) and functional MRI (fMRI) continue to advance because creative physicists, engineers, neuroscientists, clinicians, and physiologists find new ways for extracting more information from the signal. Innovations in pulse sequence design, paradigm design, and processing methods have advanced the field and firmly established fMRI as a cornerstone for understanding the human brain. In this article, the field of fMRI is described through consideration of the central problem of separating hemodynamic from neuronal information. Discussed here are examples of how pulse sequences, activation paradigms, and processing methods are integrated such that novel, high-quality information can be obtained. Examples include the extraction of information such as activation onset latency, metabolic rate, neuronal adaptation, vascular patency, vessel diameter, vigilance, and subvoxel activation. Experimental measures include time series latency, hemodynamic shape, MR phase, multivoxel patterns, ratios of activation-related R2* to R2, metabolic rate changes, fluctuation correlations and frequencies, changes in fluctuation correlations and frequencies over time, resting correlation states, echo time dependence, and more.

Anticipatory anxiety disrupts neural valuation during risky choice

Incidental negative emotions unrelated to the current task, such as background anxiety, can strongly influence decisions. This is most evident in psychiatric disorders associated with generalized emotional disturbances. However, the neural mechanisms by which incidental emotions may affect choices remain poorly understood. Here we study the effects of incidental anxiety on human risky decision making, focusing on both behavioral preferences and their underlying neural processes. Although observable choices remained stable across affective contexts with high and low incidental anxiety, we found a clear change in neural valuation signals: during high incidental anxiety, activity in ventromedial prefrontal cortex and ventral striatum showed a marked reduction in (1) neural coding of the expected subjective value (ESV) of risky options, (2) prediction of observed choices, (3) functional coupling with other areas of the valuation system, and (4) baseline activity. At the same time, activity in the anterior insula showed an increase in coding the negative ESV of risky lotteries, and this neural activity predicted whether the risky lotteries would be rejected. This pattern of results suggests that incidental anxiety can shift the focus of neural valuation from possible positive consequences to anticipated negative consequences of choice options. Moreover, our findings show that these changes in neural value coding can occur in the absence of changes in overt behavior. This suggest a possible pathway by which background anxiety may lead to the development of chronic reward desensitization and a maladaptive focus on negative cognitions, as prevalent in affective and anxiety disorders.

Upper bounds on noise and model misspecification for robust estimation of real-time brain activity from functional near infrared spectroscopy

The robust characterization of real-time brain activity carries potential for many applications. However, the contamination of measured signals by various instrumental, environmental, and physiological sources of noise introduces a substantial amount of signal variance and, consequently, challenges real-time estimation of contributions from underlying neuronal sources. Functional near infrared spectroscopy (fNIRS) is an emerging imaging modality whose real-time potential is yet to be fully explored. The objectives of the current study are to (i) validate a time-dependent linear model of hemodynamic responses in fNIRS, and (ii) test the robustness of this approach against measurement noise (instrumental and physiological) and mis-specification of the hemodynamic response basis functions (amplitude, latency, and duration). We propose a linear hemodynamic model with time-varying parameters, which are estimated (adapted and tracked) using a dynamic recursive least square algorithm. Owing to the linear nature of the activation model, the problem of achieving robust convergence to an accurate estimation of the model parameters is recast as a problem of parameter error stability around the origin. We show that robust convergence of the proposed method is guaranteed in the presence of an acceptable degree of model misspecification and we derive an upper bound on noise under which reliable parameters can still be inferred. While here applied to fNIRS, the proposed methodology is applicable to other hemodynamic-based imaging technologies such as functional magnetic resonance imaging.

An investigation of the neural substrates of mind wandering induced by viewing traditional Chinese landscape paintings

The present study was conducted to investigate whether the calming effect induced by viewing traditional Chinese landscape paintings would make disengagement from that mental state more difficult, as measured by performance on a cognitive control task. In Experiment 1 we examined the subjective experience of viewing traditional Chinese landscape paintings vs. realistic oil landscape paintings in a behavioral study. Our results confirmed that, as predicted, traditional Chinese landscape paintings induce greater levels of relaxation and mind wandering and lower levels of object-oriented absorption and recognition, compared to realistic oil landscape paintings. In Experiment 2 we used functional Magnetic Resonance Imaging to explore the behavioral and neural effects of viewing traditional Chinese landscape paintings on a task requiring cognitive control (i.e., the flanker task)—administered immediately following exposure to paintings. Contrary to our prediction, the behavioral data demonstrated that compared to realistic oil landscape paintings, exposure to traditional Chinese landscape paintings had no effect on performance on the flanker task. However, the neural data demonstrated an interaction effect such that there was greater activation in the inferior parietal cortex and the superior frontal gyrus on incongruent compared with congruent flanker trials when participants switched from viewing traditional Chinese landscape paintings to the flanker task than when they switched from realistic oil landscape paintings. These results suggest that switching from traditional Chinese landscape paintings placed greater demands on the brain’s attention and working memory networks during the flanker task than did switching from realistic oil landscape paintings.

Task dependent lexicality effects support interactive models of reading: a meta-analytic neuroimaging review

Models of reading must explain how orthographic input activates a phonological representation, and elicits the retrieval of word meaning from semantic memory. Comparisons between tasks that theoretically differ with respect to the degree to which they rely on connections between orthographic, phonological and semantic systems during reading can thus provide valuable insight into models of reading, but such direct comparisons are not well-represented in the literature. An ALE meta-analysis explored lexicality effects directly contrasting words and pseudowords using the lexical decision task and overt or covert naming, which we assume rely most on the semantic and phonological systems, respectively. Interactions between task and lexicality effects demonstrate that different demands of the lexical decision and naming tasks lead to different manifestations of lexicality effects.

Prolonged hemodynamic response during incidental facial emotion processing in inter-episode bipolar I disorder

This fMRI study examined whether hemodynamic responses to affectively-salient stimuli were abnormally prolonged in remitted bipolar disorder, possibly representing a novel illness biomarker. A group of 18 DSM-IV bipolar I-diagnosed adults in remission and a demographically-matched control group performed an event-related fMRI gender-discrimination task in which face stimuli had task-irrelevant neutral, happy or angry expressions designed to elicit incidental emotional processing. Participants' brain activation was modeled using a "fully informed" SPM5 basis set. Mixed-model ANOVA tested for diagnostic group differences in BOLD response amplitude and shape within brain regions-of-interest selected from ALE meta-analysis of previous comparable fMRI studies. Bipolar-diagnosed patients had a generally longer duration and/or later-peaking hemodynamic response in amygdala and numerous prefrontal cortex brain regions. Data are consistent with existing models of bipolar limbic hyperactivity, but the prolonged frontolimbic response more precisely details abnormalities recognized in previous studies. Prolonged hemodynamic responses were unrelated to stimulus type, task performance, or degree of residual mood symptoms, suggesting an important novel trait vulnerability brain dysfunction in bipolar disorder. Bipolar patients also failed to engage pregenual cingulate and left orbitofrontal cortex-regions important to models of automatic emotion regulation-while engaging a delayed dorsolateral prefrontal cortex response not seen in controls. These results raise questions about whether there are meaningful relationships between bipolar dysfunction of specific ventromedial prefrontal cortex regions believed to automatically regulate emotional reactions and the prolonged responses in more lateral aspects of prefrontal cortex.

Influence of neurobehavioral incentive valence and magnitude on alcohol drinking behavior

The monetary incentive delay (MID) task is a widely used probe for isolating neural circuitry in the human brain associated with incentive motivation. In the present functional magnetic resonance imaging (fMRI) study, 82 young adults, characterized along dimensions of impulsive sensation seeking, completed a MID task. fMRI and behavioral incentive functions were decomposed into incentive valence and magnitude parameters, which were used as predictors in linear regression to determine whether mesolimbic response is associated with problem drinking and recent alcohol use. Alcohol use was best explained by higher fMRI response to anticipation of losses and feedback on high gains in the thalamus. In contrast, problem drinking was best explained by reduced sensitivity to large incentive values in mesolimbic regions in the anticipation phase and increased sensitivity to small incentive values in the dorsal caudate nucleus in the feedback phase. Altered fMRI responses to monetary incentives in mesolimbic circuitry, particularly those alterations associated with problem drinking, may serve as potential early indicators of substance abuse trajectories.

A semi-parametric nonlinear model for event-related fMRI

Nonlinearity in evoked hemodynamic responses often presents in event-related fMRI studies. Volterra series, a higher-order extension of linear convolution, has been used in the literature to construct a nonlinear characterization of hemodynamic responses. Estimation of the Volterra kernel coefficients in these models is usually challenging due to the large number of parameters. We propose a new semi-parametric model based on Volterra series for the hemodynamic responses that greatly reduces the number of parameters and enables "information borrowing" among subjects. This model assumes that in the same brain region and under the same stimulus, the hemodynamic responses across subjects share a common but unknown functional shape that can differ in magnitude, latency and degree of interaction. We develop a computationally-efficient strategy based on splines to estimate the model parameters, and a hypothesis test on nonlinearity. The proposed method is compared with several existing methods via extensive simulations, and is applied to a real event-related fMRI study.

Larger neural responses produce BOLD signals that begin earlier in time

Functional MRI analyses commonly rely on the assumption that the temporal dynamics of hemodynamic response functions (HRFs) are independent of the amplitude of the neural signals that give rise to them. The validity of this assumption is particularly important for techniques that use fMRI to resolve sub-second timing distinctions between responses, in order to make inferences about the ordering of neural processes. Whether or not the detailed shape of the HRF is independent of neural response amplitude remains an open question, however. We performed experiments in which we measured responses in primary visual cortex (V1) to large, contrast-reversing checkerboards at a range of contrast levels, which should produce varying amounts of neural activity. Ten subjects (ages 22-52) were studied in each of two experiments using 3 Tesla scanners. We used rapid, 250 ms, temporal sampling (repetition time, or TR) and both short and long inter-stimulus interval (ISI) stimulus presentations. We tested for a systematic relationship between the onset of the HRF and its amplitude across conditions, and found a strong negative correlation between the two measures when stimuli were separated in time (long- and medium-ISI experiments, but not the short-ISI experiment). Thus, stimuli that produce larger neural responses, as indexed by HRF amplitude, also produced HRFs with shorter onsets. The relationship between amplitude and latency was strongest in voxels with lowest mean-normalized variance (i.e., parenchymal voxels). The onset differences observed in the longer-ISI experiments are likely attributable to mechanisms of neurovascular coupling, since they are substantially larger than reported differences in the onset of action potentials in V1 as a function of response amplitude.

Greater striatopallidal adaptive coding during cue-reward learning and food reward habituation predict future weight gain

Animal experiments indicate that after repeated pairings of palatable food receipt and cues that predict palatable food receipt, dopamine signaling increases in response to predictive cues, but decreases in response to food receipt. Using functional MRI and mixed effects growth curve models with 35 females (M age=15.5±0.9; M BMI=24.5±5.4) we documented an increase in BOLD response in the caudate (r=.42) during exposure to cues predicting impending milkshake receipt over repeated exposures, demonstrating a direct measure of in vivo cue-reward learning in humans. Further, we observed a simultaneous decrease in putamen (r=-.33) and ventral pallidum (r=-.45) response during milkshake receipt that occurred over repeated exposures, putatively reflecting food reward habitation. We then tested whether cue-reward learning and habituation slopes predicted future weight over 2-year follow-up. Those who exhibited the greatest escalation in ventral pallidum responsivity to cues and the greatest decrease in caudate response to milkshake receipt showed significantly larger increases in BMI (r=.39 and -.69 respectively). Interestingly, cue-reward learning propensity and food reward habituation were not correlated, implying that these factors may constitute qualitatively distinct vulnerability pathways to excess weight gain. These two individual difference factors may provide insight as to why certain people have shown obesity onset in response to the current obesogenic environment in western cultures, whereas others have not.

Altered activation in fronto-striatal circuits during sequential processing of conflict in unmedicated adults with obsessive-compulsive disorder

BACKGROUND

The aim of this study was to examine the functioning of fronto-striatal brain circuits that support self-regulatory capacities including conflict resolution and sequential processing in unmedicated adults with obsessive-compulsive disorder (OCD).

METHODS

We compared functional magnetic resonance imaging blood oxygen level-dependent response in 22 adults with OCD with 22 healthy, age-matched control subjects during performance of a Simon Spatial Incompatibility task. We used general linear modeling to compare groups in their patterns of brain activation during correct responses to conflict-laden stimuli and explore the effects of trial sequence on group differences.

RESULTS

Behavioral performance on the Simon task did not differ between groups. In response to conflict-laden stimuli, OCD participants activated fronto-striatal regions significantly more than control subjects, specifically a right hemisphere cluster encompassing the putamen, insula, and inferior frontal gyrus. Their activation of this cluster was driven not by conflict on a current trial but by their response to the alternation of stimulus congruence (incongruent or congruent) across trial sequences (i.e., current and preceding trials) and was most accentuated in participants with more severe symptoms in the doubt/checking dimension. Functional connectivity from the putamen to other fronto-striatal regions was also greater in the OCD compared with control participants.

CONCLUSIONS

When engaging the self-regulatory control necessary to resolve conflict and process alternating stimuli, OCD participants displayed excessive activation in a fronto-striatal circuit that differs from the orbitofrontal cortex-anterior cingulate cortex-caudate circuit typically implicated in OCD. Dysfunction in this circuit was associated with processing changes in the stimulus context. We speculate that this dysfunction might be related to the cognitive inflexibility typical of persons with OCD.

Spatio-temporal processing of words and nonwords: hemispheric laterality and acute alcohol intoxication

This study examined neurofunctional correlates of reading by modulating semantic, lexical, and orthographic attributes of letter strings. It compared the spatio-temporal activity patterns elicited by real words (RW), pseudowords, orthographically regular, pronounceable nonwords (PN) that carry no meaning, and orthographically illegal, nonpronounceable nonwords (NN). A double-duty lexical decision paradigm instructed participants to detect RW while ignoring nonwords and to additionally respond to words that refer to animals (AW). Healthy social drinkers (N=22) participated in both alcohol (0.6 g/kg ethanol for men, 0.55 g/kg for women) and placebo conditions in a counterbalanced design. Whole-head MEG signals were analyzed with an anatomically-constrained MEG method. Simultaneously acquired ERPs confirm previous evidence. Spatio-temporal MEG estimates to RW and PN are consistent with the highly replicable left-lateralized ventral visual processing stream. However, the PN elicit weaker activity than other stimuli starting at ~230 ms and extending to the M400 (magnetic equivalent of N400) in the left lateral temporal area, indicating their reduced access to lexicosemantic stores. In contrast, the NN uniquely engage the right hemisphere during the M400. Increased demands on lexicosemantic access imposed by AW result in greater activity in the left temporal cortex starting at ~230 ms and persisting through the M400 and response preparation stages. Alcohol intoxication strongly attenuates early visual responses occipito-temporally overall. Subsequently, alcohol selectively affects the left prefrontal cortex as a function of orthographic and semantic dimensions, suggesting that it modulates the dynamics of the lexicosemantic processing in a top-down manner, by increasing difficulty of semantic retrieval.

Categorical clustering of the neural representation of color

Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons.

Sleep-dependent Neurophysiological Processes in Implicit Sequence Learning

Behavioral studies have cast doubts about the role that posttraining sleep may play in the consolidation of implicit sequence learning. Here, we used event-related fMRI to test the hypothesis that sleep-dependent functional reorganization would take place in the underlying neural circuits even in the possible absence of obvious behavioral changes. Twenty-four healthy human adults were scanned at Day 1 and then at Day 4 during an implicit probabilistic serial RT task. They either slept normally (RS) or were sleep-deprived (SD) on the first posttraining night. Unknown to them, the sequential structure of the material was based on a probabilistic finite-state grammar, with 15% chance on each trial of replacing the rules-based grammatical (G) stimulus with a nongrammatical (NG) one. Results indicated a gradual differentiation across sessions between RTs (faster RTs for G than NG), together with NG-related BOLD responses reflecting sequence learning. Similar behavioral patterns were observed in RS and SD participants at Day 4, indicating time- but not sleep-dependent consolidation of performance. Notwithstanding, we observed at Day 4 in the RS group a diminished differentiation between G- and NG-related neurophysiological responses in a set of cortical and subcortical areas previously identified as being part of the network involved in implicit sequence learning and its offline processing during sleep, indicating a sleep-dependent processing of both regular and deviant stimuli. Our results suggest the sleep-dependent development of distinct neurophysiological processes subtending consolidation of implicit motor sequence learning, even in the absence of overt behavioral differences.

Generalized spike and waves: effect of discharge duration on brain networks as revealed by BOLD fMRI

In the past decade, the possibility of combining recordings of EEG and functional MRI (EEG-fMRI), has brought a new insight into the brain network underlying generalized spike wave discharges (GSWD). Nevertheless, how GSWD duration influences this network is not fully understood. In this study we aim to investigate whether GSWD duration had a threshold (non-linear) and/or a linear effect on the amplitude of the associated BOLD changes in any brain regions. This could help in elucidating if there is an hemodynamic background supporting the differentiation between interictal and ictal events. We studied a population of 42 patients with idiopathic generalized epilepsies (IGE) who underwent resting-state EEG-fMRI recordings in three centres (London, UK; Modena, Italy; Rome, Italy), applying a parametric analysis of the GSWD duration. Patients were classified as having Childhood Absence epilepsy, Juvenile Absence Epilepsy, or Juvenile Myoclonic Epilepsy. At the population level linear GSWD duration-related BOLD signal changes were found in a network of brain regions: mainly BOLD increase in thalami and cerebral ventricles, and BOLD decrease in posterior cingulate, precuneus and bilateral parietal regions. No region of significant BOLD change was found in the group analysis for the non-linear effect of GSWD duration. To explore the possible effect of both the different IGE sub-syndromes and the different protocols and scanning equipment used in the study, a full-factorial ANOVA design was performed revealing no significant differences. These findings support the idea that the amplitude of the BOLD changes is linearly related to the GSWD duration with no universal threshold effect of spike and wave duration on the brain network supporting this activity.

Cognitive empathy modulates the processing of pragmatic constraints during sentence comprehension

Previous studies have shown that brain regions for mentalizing, including temporoparietal junction (TPJ) and medial prefrontal cortex (mPFC), are activated in understanding the nonliteral meaning of sentences. A different set of brain regions, including left inferior frontal gyrus (IFG), is activated for dealing with pragmatic incongruence. Here we demonstrate that individuals' cognitive empathic ability modulates the brain activity underlying the processing of pragmatic constraints during sentence comprehension. The lian … dou … construction in Chinese (similar to English even) normally describes an event of low expectedness; it also introduces a pragmatic scale against which the likelihood of an underspecified event can be inferred. By embedding neutral or highly likely events in the construction, we created underspecified and incongruent sentences and compared both with control sentences in which events of low expectedness were described. Imaging results showed that (i) left TPJ was activated for the underspecified sentences, and the activity in mPFC correlated with individuals' fantasizing ability and (ii) anterior cingulate cortex (ACC) was activated for the incongruent sentences, and the activity in bilateral IFG correlated with individuals' perspective taking ability. These findings suggest that brain activations in making pragmatic inference and in dealing with pragmatic failure are modulated by different components of cognitive empathy.

A survey of the sources of noise in fMRI

Functional magnetic resonance imaging (fMRI) is a noninvasive method for measuring brain function by correlating temporal changes in local cerebral blood oxygenation with behavioral measures. fMRI is used to study individuals at single time points, across multiple time points (with or without intervention), as well as to examine the variation of brain function across normal and ill populations. fMRI may be collected at multiple sites and then pooled into a single analysis. This paper describes how fMRI data is analyzed at each of these levels and describes the noise sources introduced at each level.

Networks involved in olfaction and their dynamics using independent component analysis and unified structural equation modeling

The study of human olfaction is complicated by the myriad of processing demands in conscious perceptual and emotional experiences of odors. Combining functional magnetic resonance imaging with convergent multivariate network analyses, we examined the spatiotemporal behavior of olfactory-generated blood-oxygenated-level-dependent signal in healthy adults. The experimental functional magnetic resonance imaging (fMRI) paradigm was found to offset the limitations of olfactory habituation effects and permitted the identification of five functional networks. Analysis delineated separable neuronal circuits that were spatially centered in the primary olfactory cortex, striatum, dorsolateral prefrontal cortex, rostral prefrontal cortex/anterior cingulate, and parietal-occipital junction. We hypothesize that these functional networks subserve primary perceptual, affective/motivational, and higher order olfactory-related cognitive processes. Results provided direct evidence for the existence of parallel networks with top-down modulation for olfactory processing and clearly distinguished brain activations that were sniffing-related versus odor-related. A comprehensive neurocognitive model for olfaction is presented that may be applied to broader translational studies of olfactory function, aging, and neurological disease.

Verbal descriptors influence hypothalamic response to low-calorie drinks

Messages describing foods constitute a pervasive form of reward cueing. Different descriptions may produce particular appeal depending upon the individual. To examine the extent to which verbal descriptors and individual differences interact to influence food preferences, we used functional magnetic resonance imaging to measure brain responses to the same low-calorie drinks preceded by the spoken verbal descriptor "treat" or "healthy" in 27 subjects varying in BMI, eating style and reward sensitivity. Subjects also sampled a prototypical milkshake treat. Despite the fact that the verbal descriptor had no influence on pleasantness ratings, preferential responses to the low-calorie drinks labeled "treat" vs. "healthy" were observed in the midbrain and hypothalamus. These same regions were also preferentially responsive to the prototypical treat. These results reveal a previously undocumented influence of verbal descriptors on brain circuits regulating energy homeostasis.

Spatiotemporal Segregation of Neural Response to Auditory Stimulation: An fMRI Study Using Independent Component Analysis and Frequency-Domain Analysis

Although auditory processing has been widely studied with conventional parametric methods, there have been a limited number of independent component analysis (ICA) applications in this area. The purpose of this study was to examine spatiotemporal behavior of brain networks in response to passive auditory stimulation using ICA. Continuous broadband noise was presented binaurally to 19 subjects with normal hearing. ICA was performed to segregate spatial networks, which were subsequently classified according to their temporal relation to the stimulus using power spectrum analysis. Classification of separated networks resulted in 3 stimulus-activated, 9 stimulus-deactivated, 2 stimulus-neutral (stimulus-dependent but not correlated with the stimulation timing), and 2 stimulus-unrelated (fluctuations that did not follow the stimulus cycles) components. As a result of such classification, spatiotemporal subdivisions were observed in a number of cortical structures, namely auditory, cingulate, and sensorimotor cortices, where parts of the same cortical network responded to the stimulus with different temporal patterns. The majority of the classified networks seemed to comprise subparts of the known resting-state networks (RSNs); however, they displayed different temporal behavior in response to the auditory stimulus, indicating stimulus-dependent temporal segregation of RSNs. Only one of nine deactivated networks coincided with the “classic” default-mode network, suggesting the existence of a stimulus-dependent default-mode network, different from that commonly accepted.

The amygdalostriatal and corticostriatal effective connectivity in anticipation and evaluation of facial attractiveness

Decision-making consists of several stages of information processing, including an anticipation stage and an outcome evaluation stage. Previous studies showed that the ventral striatum (VS) is pivotal to both stages, bridging motivation and action, and it works in concert with the ventral medial prefrontal cortex (vmPFC) and the amygdala. However, evidence concerning how the VS works together with the vmPFC and the amygdala came mainly from neuropathology and animal studies; little is known about the dynamics of this network in the functioning human brain. Here we used fMRI combined with dynamic causal modeling (DCM) to investigate the information flow along amygdalostriatal and corticostriatal pathways in a facial attractiveness guessing task. Specifically, we asked participants to guess whether a blurred photo of female face was attractive and to wait for a few seconds ("anticipation stage") until an unblurred photo of feedback face, which was either attractive or unattractive, was presented ("outcome evaluation stage"). At the anticipation stage, the bilateral amygdala and VS showed higher activation for the "attractive" than for the "unattractive" guess. At the outcome evaluation stage, the vmPFC and the bilateral VS were more activated by feedback faces whose attractiveness was congruent with the initial guess than by incongruent faces; however, this effect was only significant for attractive faces, not for unattractive ones. DCM showed that at the anticipation stage, the choice-related information entered the amygdalostriatal pathway through the amygdala and was projected to the VS. At the evaluation stage, the outcome-related information entered the corticostriatal pathway through the vmPFC. Bidirectional connectivities existed between the vmPFC and VS, with the VS-to-vmPFC connectivity weakened by unattractive faces. These findings advanced our understanding of the reward circuitry by demonstrating the pattern of information flow along the amygdalostriatal and corticostriatal pathways at different stages of decision-making.

Age-related changes of blood-oxygen-level-dependent signal dynamics during optokinetic stimulation

The present study aimed to reveal the effects of age on the temporal profile of the positive blood-oxygen-level-dependent response (PBR) during low-velocity optokinetic nystagmus (OKN) in healthy subjects. We were specifically interested in comparing these effects with the effects of age on the PBR elicited by pure visual and motor tasks. Therefore, we conducted 2 additional control experiments: a checkerboard experiment (visual stimulation) and a finger-tapping (motor task) experiment. Whereas the oculomotor performance of the subjects remained unaltered, the temporal profile of the PBR changed significantly with increasing age in visual and oculomotor areas. None of the control experiments revealed significant age-related PBR changes. Thus, this study demonstrates that the PBR changes during OKN occur before any changes in the oculomotor performance can be detected. These effects of age are specific for the OKN task and probably reflect both changes in the neurovascular coupling and changes in the neural processing during OKN.

fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG

Neuronal activation sequence information is essential for understanding brain functions. Extracting such timing information from blood oxygenation level dependent (BOLD) fMRI is confounded by interregional neurovascular differences and poorly understood relations between BOLD and electrophysiological response delays. Here, we recorded whole-head BOLD fMRI at 100 ms resolution and magnetoencephalography (MEG) during a visuomotor reaction-time task. Both methods detected the same activation sequence across five regions, from visual towards motor cortices, with linearly correlated interregional BOLD and MEG response delays. The smallest significant interregional BOLD delay was 100 ms; all delays ≥400 ms were significant. Switching the order of external events reversed the sequence of BOLD activations, indicating that interregional neurovascular differences did not confound the results. This may open new avenues for using fMRI to follow rapid activation sequences in the brain.

A semi-parametric model of the hemodynamic response for multi-subject fMRI data

A semi-parametric model for estimating hemodynamic response function (HRF) from multi-subject fMRI data is introduced within the context of the General Linear Model. The new model assumes that the HRFs for a fixed brain voxel under a given stimulus share the same unknown functional form across subjects, but differ in height, time to peak, and width. A nonparametric spline-smoothing method is developed to evaluate this common functional form, based on which subject-specific characteristics of the HRFs can be estimated. This semi-parametric model explicitly characterizes the common properties shared across subjects and is flexible in describing various brain hemodynamic activities across different regions and stimuli. In addition, the temporal differentiability of the employed spline basis enables an easy-to-compute way of evaluating latency and width differences in hemodynamic activity. The proposed method is applied to data collected as part of an ongoing study of socially mediated emotion regulation. Comparison with several existing methods is conducted through simulations and real data analysis.

Linear mixed-effects modeling approach to FMRI group analysis

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details.

Accurate decoding of sub-TR timing differences in stimulations of sub-voxel regions from multi-voxel response patterns

We investigated the decoding of ocular dominance stimulations with millisecond-order timing difference from the blood oxygen level dependent (BOLD) signal in human functional magnetic resonance imaging (fMRI). In our experiment, ocular dominance columns were activated by monocular visual stimulation with 500- or 100- ms onset differences. We observed that the event-related hemodynamic response (HDR) in the human visual cortex was sensitive to the subtle onset difference. The HDR shapes were related to the stimulus timings in various manners: the timing difference was represented in either the amplitude of positive peak, amplitude of negative peak, delay of peak time, or response duration of HDR. These complex relationships were different across voxels and subjects. To find an informative feature of HDR for discriminating the subtle timing difference of ocular dominance stimulations, we examined various characteristics of HDR including response amplitude, time to peak, full width at half-maximum response, as inputs for decoding analysis. Using a canonical HDR function for estimating the voxel's response did not yield good decoding scores, suggesting that information may reside in the variability of HDR shapes. Using all the values from the deconvolved HDR also showed low performance, which could be due to an over-fitting problem with the large data dimensionality. When using either positive or negative peak amplitude of the deconvolved HDR, high decoding performance could be achieved for both the 500ms and the 100ms onset differences. The high accuracy even for the 100ms difference, given that the signal was sampled at a TR of 250ms and 2×2×3-mm voxels, implies a possibility of spatiotemporally hyper-resolution decoding. Furthermore, both down-sampling and smoothing did not affect the decoding accuracies very much. These results suggest a complex spatiotemporal relationship between the multi-voxel pattern of the BOLD response and the population activation of neuronal columns. The demonstrated possibility of decoding stimulations for columnar-level organization with 100-ms onset difference using lower resolution imaging data may broaden the scope of application of the BOLD fMRI.

Measuring relative timings of brain activities using fMRI

Functional MRI (fMRI) has previously been shown to be able to measure hundreds of milliseconds differences in timings of activities in different brain regions, even though the underlying blood oxygenation level-dependent (BOLD) response is delayed and dispersed on the order of seconds. This capability may contribute towards the study of communication within the brain by assessing the temporal sequences of various brain processes (mental chronometry). The practical limit of fMRI for detecting the relative timing of brain activity is not known. We aimed to detect fine differences in the timings of brain activities beyond those previously measured from fMRI data in human subjects. We introduced known delays between the onsets of visual stimuli in a controlled, sparse event-related design and investigated if the temporal shifts in the corresponding average BOLD signals were detectable. To maximize sensitivity, we used high spatial and temporal resolution fMRI at ultrahigh field (7 T), in conjunction with a novel data-driven technique for voxel selection using graph-based visualizations of self-organizing maps and Granger causality to measure relative timing. This approach detected timing differences as small as 28ms in visual cortex in individual subjects. For signal extraction, the self-organizing map approach outperformed other common techniques including independent component analysis, voxelwise univariate linear regression analysis and a separate localizer scan. For relative timing measurement, Granger causality outperformed time-to-peak calculations derived from an inverse logit curve fit. We conclude that high-resolution imaging at ultrahigh field, signal extraction via self-organizing map, and appropriate use of Granger causality permit the detection of small timing differences in fMRI data, despite the intrinsically slow hemodynamic response.

Argument structure and morphological factors in noun and verb processing: an fMRI study

In a functional MRI (fMRI) study, we have investigated the grammatical categories of object noun, event noun and verb in order to assess the cortical regions of activation supporting their processing. Twelve Italian healthy participants performed a lexical decision task. They had to decide whether a string was an Italian word or not. Words could be objects like medaglia (medal), or events like the noun pianto (cry); or the verb dormire (to sleep). Noun and verb comparison shows differences in regions of activation in the left Inferior Frontal cortex and in the extent of the same areas. We have found specific areas of activation for object noun, and similarities in the pattern of activation for event noun and verb. The activations induced by pseudowords highly resembled the areas activated by the corresponding word category. The implications of the results are discussed in light of the recent debate on the role of grammatical category in the brain.

Attention to language: novel MEG paradigm for registering involuntary language processing in the brain

Previous research indicates that, under explicit instructions to listen to spoken stimuli or in speech-oriented behavioural tasks, the brain's responses to senseless pseudowords are larger than those to meaningful words; the reverse is true in non-attended conditions. These differential responses could be used as a tool to trace linguistic processes in the brain and their interaction with attention. However, as previous studies relied on explicit instructions to attend or ignore the stimuli, a technique for automatic attention modulation (i.e., not dependent on explicit instruction) would be more advantageous, especially when cooperation with instructions may not be guaranteed (e.g., neurological patients, children etc). Here we present a novel paradigm in which the stimulus context automatically draws attention to speech. In a non-attend passive auditory oddball sequence, rare words and pseudowords were presented among frequent non-speech tones of variable frequency and length. The low percentage of spoken stimuli guarantees an involuntary attention switch to them. The speech stimuli, in turn, could be disambiguated as words or pseudowords only in their end, at the last phoneme, after the attention switch would have already occurred. Our results confirmed that this paradigm can indeed be used to induce automatic shifts of attention to spoken input. At ~250ms after the stimulus onset, a P3a-like neuromagnetic deflection was registered to spoken (but not tone) stimuli indicating an involuntary attention shift. Later, after the word-pseudoword divergence point, we found a larger oddball response to pseudowords than words, best explained by neural processes of lexical search facilitated through increased attention. Furthermore, we demonstrate a breakdown of this orderly pattern of neurocognitive processes as a result of sleep deprivation. The new paradigm may thus be an efficient way to assess language comprehension processes and their dynamic interaction with those of attention allocation. It does it in an automatic and task-free fashion, indicating its potential benefit for assessing uncooperative clinical populations.

Fractional-order time series models for extracting the haemodynamic response from functional magnetic resonance imaging data

The postprocessing of functional magnetic resonance imaging (fMRI) data to study the brain functions deals mainly with two objectives: signal detection and extraction of the haemodynamic response. Signal detection consists of exploring and detecting those areas of the brain that are triggered due to an external stimulus. Extraction of the haemodynamic response deals with describing and measuring the physiological process of activated regions in the brain due to stimulus. The haemodynamic response represents the change in oxygen levels since the brain functions require more glucose and oxygen upon stimulus that implies a change in blood flow. In the literature, different approaches to estimate and model the haemodynamic response have been proposed. These approaches can be discriminated in model structures that either provide a proper representation of the obtained measurements but provide no or a limited amount of physiological information, or provide physiological insight but lacks a proper fit to the data. In this paper, a novel model structure is studied for describing the haemodynamics in fMRI measurements: fractional models. We show that these models are flexible enough to describe the gathered data with the additional merit of providing physiological information.

A voxel-based lesion study on facial emotion recognition after penetrating brain injury

The ability to read emotions in the face of another person is an important social skill that can be impaired in subjects with traumatic brain injury (TBI). To determine the brain regions that modulate facial emotion recognition, we conducted a whole-brain analysis using a well-validated facial emotion recognition task and voxel-based lesion symptom mapping (VLSM) in a large sample of patients with focal penetrating TBIs (pTBIs). Our results revealed that individuals with pTBI performed significantly worse than normal controls in recognizing unpleasant emotions. VLSM mapping results showed that impairment in facial emotion recognition was due to damage in a bilateral fronto-temporo-limbic network, including medial prefrontal cortex (PFC), anterior cingulate cortex, left insula and temporal areas. Beside those common areas, damage to the bilateral and anterior regions of PFC led to impairment in recognizing unpleasant emotions, whereas bilateral posterior PFC and left temporal areas led to impairment in recognizing pleasant emotions. Our findings add empirical evidence that the ability to read pleasant and unpleasant emotions in other people's faces is a complex process involving not only a common network that includes bilateral fronto-temporo-limbic lobes, but also other regions depending on emotional valence.

Complex-number representation of informed basis functions in general linear modeling of Functional Magnetic Resonance Imaging

Functional Magnetic Resonance Imaging (fMRI), measuring Blood Oxygen Level-Dependent (BOLD), is a widely used tool to reveal spatiotemporal pattern of neural activity in human brain. Standard analysis of fMRI data relies on a general linear model and the model is constructed by convolving the task stimuli with a hypothesized hemodynamic response function (HRF). To capture possible phase shifts in the observed BOLD response, the informed basis functions including canonical HRF and its temporal derivative, have been proposed to extend the hypothesized hemodynamic response in order to obtain a good fitting model. Different t contrasts are constructed from the estimated model parameters for detecting the neural activity between different task conditions. However, the estimated model parameters corresponding to the orthogonal basis functions have different physical meanings. It remains unclear how to combine the neural features detected by the two basis functions and construct t contrasts for further analyses. In this paper, we have proposed a novel method for representing multiple basis functions in complex domain to model the task-driven fMRI data. Using this method, we can treat each pair of model parameters, corresponding respectively to canonical HRF and its temporal derivative, as one complex number for each task condition. Using the specific rule we have defined, we can conveniently perform arithmetical operations on the estimated model parameters and generate different t contrasts. We validate this method using the fMRI data acquired from twenty-two healthy participants who underwent an auditory stimulation task.

Whole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysis

The brain is the body's largest energy consumer, even in the absence of demanding tasks. Electrophysiologists report on-going neuronal firing during stimulation or task in regions beyond those of primary relationship to the perturbation. Although the biological origin of consciousness remains elusive, it is argued that it emerges from complex, continuous whole-brain neuronal collaboration. Despite converging evidence suggesting the whole brain is continuously working and adapting to anticipate and actuate in response to the environment, over the last 20 y, task-based functional MRI (fMRI) have emphasized a localizationist view of brain function, with fMRI showing only a handful of activated regions in response to task/stimulation. Here, we challenge that view with evidence that under optimal noise conditions, fMRI activations extend well beyond areas of primary relationship to the task; and blood-oxygen level-dependent signal changes correlated with task-timing appear in over 95% of the brain for a simple visual stimulation plus attention control task. Moreover, we show that response shape varies substantially across regions, and that whole-brain parcellations based on those differences produce distributed clusters that are anatomically and functionally meaningful, symmetrical across hemispheres, and reproducible across subjects. These findings highlight the exquisite detail lying in fMRI signals beyond what is normally examined, and emphasize both the pervasiveness of false negatives, and how the sparseness of fMRI maps is not a result of localized brain function, but a consequence of high noise and overly strict predictive response models.